Method for analyzing characteristics of a moving object, such as a log

ABSTRACT

A method for determining the properties of a log, in which a moving log is radiographed by at least more than one X-radiation source, and the radiographic information is received by a detector array measuring radiation. Stemwood and knots of the log are calculated by a principle which is based on a known geometry and density of stemwood and knots. After measurement, the effect of stemwood in radiographic projections, and hence the analysis for locating knots, is eliminated by filtering. The knot mass is then converted from radiographic projections into volumetric elements of a cylindrical coordinate system and, from the value of each volumetric element, an evidence value representative of the presence of a knot in the element is derived. The evidence values of mutually associated elements are then combined, thus producing an aggregate evidence value which permits the knots to be located.

This application is the national phase under 35 U.S.C. §371 of prior PCTInternational Application No. PCT/FI97/00132 which has an Internationalfiling date of Feb. 27, 1997 which designated the United States ofAmerica, the entire contents of which are hereby incorporated byreference.

FIELD OF THE INVENTION

The present invention relates to a procedure for determining theproperties of a moving object, such as a log.

BACKGROUND OF THE INVENTION

In the related art, methods are known whereby logs are observed visuallyor optically in order to sort them according to their quality. In amethod based on visual inspection, the person performing the sortingdirects the logs to different piles on the basis of visual observation.However, this method does not reveal the internal properties of thelogs. In optical measurement of dimensions, the measurement is takenfrom the surface of the bark, which means that variations in barkthickness may result in considerable errors in the determination of thedimensions and volume of the log. These methods for the inspection oflogs are mainly focused on measuring log thickness, and the measurementdata is communicated to a sorter, who directs the logs manually toappropriate piles according to this information. These methods generallyprovide no other information about the logs. According toinvestigations, another drawback is that when the sorting is done by ahuman sorter, only about half of the logs are sorted fairly correctlywith regard to the desired result.

A further drawback with the above methods is that, even if metaldetectors are used, it is not possible to identify all foreign objects,such as rocks and non-ferrous metals, that may be present in the logs.Therefore, such objects remain inside the log and may cause damage inthe equipment used for further processing of the logs. Finnish patentapplication no. FI893938 (corresponding to U.S. Pat. No. 5,023,805)presents a method based on three-projection X-ray photography, known initself in prior art. In this method, from each radiographic projection,the knot terminations are first determined via a longitudinalreconstruction of the log, whereupon knot vectors matching these pointsare calculated. The weakness of this method consists in the fact thatthe terminations cannot be determined sufficiently accurately andunambiguously from real logs. Among the reasons for this are overlappingknots and the moisture of fresh wood, which obliterates parts of theknot. Accordingly, what is needed is a method for determining theproperties of a moving object such as a log such that the aforementioneddrawbacks can be avoided or eliminated.

The object of the present invention is to eliminate the drawbacks of themethods described above and to achieve a reliable and effective methodfor determining the properties of logs relating to their quality. Themethod involves using knowledge relating to the geometry, density andother properties of the moving object, as well as inter-dependencybetween the properties, to allow sorting according to quality.

The operation, measuring and data processing performed by equipment ofthe invention is based on wood-related knowledge defined by woodquality, and on radiological application of this knowledge. The methodcomprises a radiological, adaptive expert system based on a knowledge ofwood. The procedure can also be applied to other objects or materialsmoved as bulk goods.

The method has the advantage that it enables the internal defects ofbulk goods moving on a conveyor line to be measured and identified usingonly few projections. This allows reliable determination of qualityproperties of logs moving at sawing speed. The measurements of the logcan also be taken from the log surface beneath the bark, so that thetrue dimensions of the wooden part of the log can be accuratelymeasured. Instead of using knot outlines in the pictures in alongitudinal reconstruction of the log, as in the above-mentioned patentspecification, the method in accordance with the present inventionemploys the principles of fuzzy logic to locate, by means of areconstruction formed in a direction perpendicular to the longitudinalaxis and utilizing layered slices, three-dimensional objects in whichthe knot mass is concentrated.

The procedure can be used to determine internal and external propertiesof logs. The external properties include log length, diameter, conicityand ellipticity as well as bends, multiple crookedness, crooked-growthand volume. One of the advantages of the invention is that the diameter,conicity and volume measurements can be determined from a log with thebark on it for the log without bark. Thus, accurate measurements of theuseful wood portion are obtained.

Internal defects of the log include resin pockets, rotten spots,cavities and clefts and also foreign objects, such as rocks and ferrousand other metals. The procedure provides thorough and reliableinformation about the knots and knot clusters as well as their qualityinside the log. The procedure also reveals variations in density andmoisture of the wood. By sorting the logs by quality as provided by theinvention, healthy knots, dry and rotten areas and their transitionzones can be determined.

An important feature regarding measurement and costs is a fast loganalysis achieved at a relatively low cost. It is possible to increaseboth the intensity of X-ray radiation and the computing power to producea faster analysis, but this could lead to excessive additional costs. Inthe accordance with an embodiment of the invention, both the intensityof X-ray radiation and the computing power are optimized and to attainthe desired speed and accuracy at a relatively low cost. One of thefactors contributing to this is that the amount of measurement data canbe significantly reduced as compared with prior-art solutions.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention will become more fully understood from thedetailed description given hereinbelow and the accompanying drawingswhich are given by way of illustration only, and thus are not limitativeof the present invention and wherein:

FIG. 1 illustrates a system of cylindric coordinates, as a way todescribe a knot in a log;

FIG. 2 shows how a log is divided into volumetric elements in cylindriccoordinates;

FIG. 3 illustrates the geometry of the log raying process;

FIG. 4 illustrates exemplary array sums of a radiographic projection,from which the locations of knots can be calculated;

FIG. 5 represents the principle of filtering out the effect of stemwoodfrom a radiographic projection;

FIG. 6 illustrates an exemplary evidence graph for volumetric elementsby sectors;

FIG. 7 describes a simplified illustration of the passage of an X-raythrough a log divided into sectors and circles; and

FIG. 8 presents a table of measurement results obtained in the caseillustrated by FIG. 7.

DETAILED DESCRIPTION

The method involves the use of tomography. In medical tomography, aproblem of the same type has been solved in which an object is X-rayedfrom many directions and the internal structure of the object iscalculated from the projections. However, the number of projections canrange in upwards of 500-1000. It is not possible to take as manyX-rayograms of a saw log, but in practice a few, e.g. about threeprojections must suffice. Referring to FIG. 3, the method according toinvention, a log 5 moving at sawing speed is radiographed by means ofonly a few, e.g. about three radiographic devices (such as X-rayapparatuses) emit a radiation capable of penetrating matter, and thepicture data is stored by means of detector arrays 8, one or moredetector arrays being used for each X-radiation source 4. It has beenestablished in practice that as few as three projections are sufficientto provide enough information to allow the quality properties of a logto be measured with acceptable accuracy.

The method is not concerned with reconstructing the log from thepictures pixel for pixel as in earlier practice, but instead use is madeof a knowledge of the typical geometry, density and other properties ofthe trunk, knots and the associated anomalies as well as theinterdependencies of said properties. Typically, the pictures areanalyzed to detect objects having the shape of knots or other anomalies,or parts of such objects. These are processed in a system of cylindricalcoordinates which are divided into discrete volumetric elements.

The process of determining the properties of a log or a correspondingobject by the method of the invention can be divided into three mainparts, which will be described in greater detail below.

Part I: Preliminary processing of the measurement data is performedusing the pixel-specific intensity data obtained from the radiograph ineach X-raying direction, on the basis of a knowledge of wood. Theanalysis is based on the relative attenuation differences caused byinternal objects in the log. For each wood quality, the radiologicalrelative differences, i.e. attenuation differences, of the boundarysurfaces/values between normal wood and internal objects in the wood canbe defined. These relative differences are compared both in thetransverse plane and in the direction of tree growth. The differencesare relative from one tree to another and in the same tree depending onits moisture. These divergent areas of interest are further studiedusing more exact calculation methods. Thus, the measurement datarelating to normal wood need not be processed further, so the processorpower should be sufficient for real-time quality sorting of logsadvancing at process speed. Using simple logic deduction rules,anomalies are identified as positive or negative anomalies and theboundary surface of the anomaly is determined.

Part II: Objects detected in the log are identified and their positionis ascertained using the other measuring directions. The objects (knot,rotten spot, rock, etc.) are identified by making use of a wood-typespecific knowledge on the basis of their location, size and relativeX-ray attenuation.

Part III: Based on wood-type specific knowledge and radiographicappearance, a semi-empirical simple mathematical model or representationhas been developed for objects in the wood and is applied to an objectdetected and identified in an area of interest, so the size and qualityof the object can be determined.

FIG. 1 presents a system of cylindrical coordinates, consisting of anangle of rotation α, radius r and longitudinal axis z. A slice of logtrunk is a cylindrical body in which the core runs along thelongitudinal axis z. Knots start at the core and grow towards thesurface with an upward gradient β and a spread angle γ. Each knot lieswithin a sector that contains no other knots, so each knot can bedescribed with a conical model. A knot may contain both healthy wood 10and rotten wood 11. As illustrated by FIG. 2, a log can be divided intocircles 1, slices 2 and sectors 3, and a section comprising each ofthese constitutes one volumetric element, whose position is defined bythe cylindrical coordinates. The slice 2 thickness along thelongitudinal axis of the log represents width of the detector elements 9of a detector array 8 in the longitudinal axis direction of the log andtherefore the longitudinal log section exposed to radiography at a pointin time.

FIG. 3 illustrates the geometry used in the radiological apparatus,showing only one X-ray for the sake of simplicity. When the descriptiondeals with the rays emitted by one X-radiation source 4 and the detectorelements 9 receiving them, which together form a detector array 8, oneradiographic projection is being referred to. Therefore, as theprocedure comprises the use of three X-radiation sources and a detectorarray corresponding to each of these, it can be said that themeasurement ultimately takes place in three radiographic projections.The X-radiation sources 4 and the corresponding detector arrays 8 areplaced at an angle of 120° relative to each other and so disposed aroundthe path of the log that the log will pass between the X-radiationsources 4 and the corresponding detector arrays 8. Thus, the X-raysemitted by the X-radiation sources penetrate the log and, depending onthe properties of the log, are attenuated in different ways on their wayto the detector arrays, whose detector elements 9 receive the radiationthus attenuated. Each detector array 8 consists of a series of detectorelements 9 placed in a curved arrangement around the log, all of thedetector elements being located at equal distances from thecorresponding X-radiation source 4 and in the same plane perpendicularto the log movement as the X-radiation source. The number ofradiographic projections used may be greater or smaller than three asneeded.

The log 5 lies on a conveyor surface 7, where it is exposed toX-radiation from an X-radiation source 4. The radiation penetrating thelog 5 is received by a detector element 9. The geometry is described bythe distance d1 between the X-radiation source 4 and the center line ofthe log 5, the distance d2 between the X-radiation source 4 and theconveyor surface 7 and the distance d3 between the X-radiation source 4and the detector array 8. Distance d1 depends on the log radius R asfollows: d1=d2-R. The detector elements 9 of the detector array 8 areindexed each one separately. The detector element 9 receives informationabout a sector element 6 of the log, but also for the entire distancecovered by the ray. The information consists of X-ray attenuation data.

A knot model is created by utilizing a knowledge of the typical geometryand density of knots and stemwood. Below are a few rules:

(a) The cross-section of the trunk is roughly elliptical. The size ofthe cross-section can be estimated as being the mean value of thediameters of the three radiographic projections. The largest one of thediameters of the radiographic projections is used to define the circlethat contains the cross-section of the reconstructed image.

(b) All knots start from the core of the trunk. The knot is a cone whichis described by an angle of rotation α, an upward gradient β, a spreadangle γ and a radial length r. The upward gradient β has certainpredetermined values in degrees.

(c) All knots in a cluster of knots start from about the same point.Adjacent knots cannot lie side by side, but a minimum value has beendefined for the rotational distance between knots.

(d) The density of the trunk varies from the core towards the externalsurface. Typical densities of sapwood, heartwood and knots have beendefined experimentally.

Before the calculation, the center of the log must be brought exactly tothe center of the calculation coordinates. This is done by moving theimage until the log center coincides with the centre of the coordinates.The log center again is obtained by determining the edges of the logfrom the radiographic projection by thresholding and then calculatingthe log diameter from the edge data obtained.

An X-ray penetrating a log undergoes greater attenuation when passingthrough a knot than when passing through other, softer wood material. Byexamining the rays received by the detector elements 9, it is possibleto obtain hints, which at this stage constitute unreliable individualpieces of information, indicating that the samples represented bycertain pixel groups or detector element groups might contain knot mass.By combining the images and hints indicating the presence of knots fromall radiographic projections, a certain truth value is obtained for thevolumetric element. By combining the truth values of adjacent volumetricelements, a truth value is obtained for the assumption that the sectoris part of a knot. The truth values are assigned values in the range-1-+1. The values -1, 0 and +1 may be defined verbally as meaning"absolutely no", "undefined" and "absolutely yes".

In the processing of log data, calculation time is saved by focusingexclusively on those parts of the log that contain knots or otheranomalies. From the radiation received by the detector array 8, arraysums are calculated, from which the positions of knots can bedetermined: since knots cause a greater attenuation than normal wood,the array sum for an image array containing knots is greater than for anadjacent array containing no knots. According to the invention, the aimis to locate those parts of the log which produce an increased arraysum, which may contain knots. FIG. 4 presents an example of thevariations of the array sums in the longitudinal direction of the log.In graph (a), the positions of knot clusters and also the log thicknessare clearly visible.

In graph (b), the variation of log thickness has been filtered out. Byperforming median filtering on the start and end coordinates of the knotclusters, graph (c) is obtained. After the positions of knot clustershave been determined, the effect of stemwood is filtered out from theradiographic projections, so that only changes caused by knots and otheranomalies remain. FIG. 5 presents a longitudinal section of a logwithout stemwood filtering (a) and another graph representing the samesection with the effect of stemwood filtered out (b). The graphrepresents a longitudinal stripe of the log as seen by one detectorelement. In other words, this is a vertical stripe picked from atwo-dimensional image. The log images contain a sufficient number ofsuch stripes side by side.

Eligible filtering methods include e.g. average or median filtering. Thefiltering is performed by observing a series of points p(i) consistingof N measuring points, i.e. index (i) is assigned values 1 . . . N. Thefiltering compensates local variations, thus permitting larger entitiesto appear more clearly. In the case of the present invention, thefiltering is performed to eliminate the effect of stemwood from theimage, so what remains is the image produced by knots and otheranomalies.

In average filtering, a new value q(i) is calculated for each point asfollows: ##EQU1##

To calculate a filtered value for a point i, an average is determined byconsidering m points on both sides of the point i. The number m is soselected that the variations to be filtered cover a length shorter thanm points.

Correspondingly, in median filtering, points p(i-m)-p(i+m) are similarlyconsidered to calculate a filtered value for points i. The numericvalues of the points are ordered in sequence according to magnitude andthe middle one is selected, called the median of this number series.Median filtering involves more computing work than average filtering,but it is not sensitive to the effects of individual large anomalies.

After the effect of stemwood portions has been filtered out from theradiographic projections, each knot cluster is processed separately asfollows:

a) The three filtered radiographic projections are projected back to asystem of 3-D coordinates by making use of back projection coefficientscalculated beforehand. The coefficients take the known geometricproperties of knots and trunk into account. This process divides theknot mass into volumetric elements.

b) The value of each volumetric element is indicative of the density ofthe wood in the element. Using experimental parameters, the densityvalues can be converted into evidence values, which give a probabilityas to whether the volumetric element is part of a knot.

c) By combining the evidences of individual volumetric elements, truthvalues indicating possible knot sectors are obtained. FIG. 6 shows anexample of a graph representing the truth values of log sectors. It canbe seen from the graph that sectors 5, 12, 19 and 32 may contain knots.

d) Back projection as described under item a) is repeated, but this timeonly for selected rotational angles. In this way, side projections ofthe knots are obtained. From these projections, approximate upwardgradient and spread angle values are now calculated.

The back projection and associated coefficients will be now described byreferring to FIG. 7 and 8. The basic idea of the method of the inventionderives from the fact that a knot starts from the core of the trunk andgrows regularly expanding towards the trunk surface. Therefore, thecalculation is advantageously performed using cylindric coordinatesbecause the shape of a knot resembles a sector. FIG. 7 shows only 12sectors to simplify the matter, whereas the system actually uses moresectors. Since the average knot width is 20°, a knot may occupy a spaceextending across two or three sectors. In the calculation, eachradiographic projection is first processed separately. The measurementresults are then processed to eliminate the effect of stemwood, leavingonly the values representing knots. Other anomalies are not consideredat this point in this description.

In FIG. 7, the sectors are numbered 1 . . . 12 and the circles 1 . . .4. The figure shows one ray, which is emitted by the X-radiation source4 and received by one 9 of the detector elements of a detector array. Inthe table in FIG. 8, the corresponding detector element is defined aspixel h. It is assumed that the ray has been attenuated during itspassage through the log by an amount corresponding to ten units of knotmass, i.e. p(h)=10. The attenuation caused by a unit of knot mass hasbeen determined experimentally beforehand, as stated before. However, asingle measurement as described above is not sufficient to indicatewhere the knot is or whether there is only one knot or several knots.Still, it follows from the measurement geometry that only certainelements of the cross-section are to be considered. From FIG. 7 it canbe seen that the ray passes through elements (1,2), (2,2), (2,3), (3,3),(3,4), (11,3), (11,4), (12,2) and (12,3). The first number in theelement coordinates indicates the sector while the second numberindicates the circle. Thus, the attenuation information received atpixel h can only come from these elements, from one or more of them.

As the contribution of each element to the attenuation obtained as ameasurement result is not yet known at this point, it is assumed thatthe attenuation is evenly distributed throughout the passage of the rayin the log. In the case of our example, the distance travelled by theray in the log is 73.50 mm. The measured ten units of knot mass is nowdivided among the above-mentioned elements in proportion to thedistances travelled by the ray in each element. For example, the backprojection coefficient for element (1,2) is the distance of ray travelin element (1,2) divided by the total travelling distance of the ray inthe log, i.e. 8.50mm/73.50mm=0.12. As the attenuation value was 10, theprojection result obtained for element (1,2) will be 10*0.12=1.2 (FIG. 8shows a more precise reading). The coefficients c(h,i,j) used for thedivision have been calculated in advance and placed in a table as shownin FIG. 8 as explained above.

A complete table naturally contains the coefficients for all pixel,sector and circle values h, i and j. Most of the coefficients have azero value because each ray only passes through a few elements.

The term `back projection` here means that each radiographic projectionis returned via computation to the two-dimensional section from which itwas produced. In the table in FIG. 8, back projection has been performedwith only one radiographic projection and only one detector element(pixel h). When the calculation is performed with all the radiographicprojections and detector elements, i.e. with all the values obtained,and the results are summed for each element, then for each sectorelement a numeric value describing the knot mass contained in it will beobtained. If a high numeric value is obtained, then the element islikely to be part of a knot. When several high numeric values fallwithin the same sector, this further corroborates the notion that thesector contains knot mass. The numeric values are combined via a methodcalled evidential inference. When the evidence or truth value for asector exceeds a certain predefined threshold, the sector is accepted asa knot sector.

Because a large proportion of the knot mass obtained via the first backprojection process seems to be spread even into sectors having no knots,the back projection process has to be repeated. This time, all sectorsthat are not regarded as knot sectors are omitted by setting theircoefficients c(h,i,j) to zero. In this way, the knot mass can be placedexclusively in actual knot sectors.

As stated above, the size and direction of individual knots can becharacterized in terms of radial length r and angles α, β and γ. Theseparameters can be used to calculate the assumed positions and areas ofknots on the sawn surface. This makes it possible to obtain an advanceestimate of the value of the log as timber, and in further processeseven to optimize the sawing position on the basis of the knot data.

It is obvious to a person skilled in the art that the invention is notlimited to the example described above, but that different embodimentsof the invention can be varied within the scope of the following claims.

What is claimed is:
 1. A method for determining the properties of amoving object constituted by at least a log, in which the moving objectis radiographed by means of more than one radiation source emittingradiation capable of penetrating matter, and radiographic informationtherefrom is received by means of more than one detector measuringradiation capable of penetrating matter,wherein the method involvesusing knowledge relating to a known geometry, density and otherproperties constituting at least stemwood, knots and anomaliesassociated with the knots of the moving object, as well as tointerdependencies between said properties, to allow sorting according toquality, wherein the radiographic information is analyzed to locateobjects and parts of objects having the shape of a knot or otheranomalies, which differ from the non-object containing material of theobject being inspected, and wherein the effect of stemwood on theanalysis is eliminated from the radiographic information via average ormedian filtering.
 2. The method of claim 1, furthercomprising:processing measured data by using pixel-specific attenuationinformation obtained via a radiographic projection from each radiationdirection; determining differences in attenuation between portions ofwood material containing no objects and portions within the woodmaterial containing objects; comparing the attenuation differences bothin a plane transverse to the log and in a known direction of growth;identifying divergences obtained from the attenuation differences aspositive and negative divergences based on logical inference rules;identifying objects detected in the wood and verifying their location byusing other measuring directions; and calculating the presence ofobjects in the wood material of the log based on a knowledge of knowngeometry and density of stemwood and knots in the log.
 3. The method ofclaim 2, wherein a knot mass is converted from the radiographicprojections to a plurality of volumetric elements in a system ofcylindrical coordinates,wherein, from the value of each volumetricelement, an evidence value representative of the presence of a knot inthe element is derived, wherein the evidence values of mutuallyassociated elements are combined to produce an evidence value for theaggregate, and, wherein directions of the knots are determined accordingto the highest total evidence values.
 4. A method of analyzing a log todetermine the presence of objects constituting at least stemwood andknots inside the log, comprising:radiographing the log from at least onedirection with at least one radiation source which penetrates the logtherethrough; obtaining measurement data from said radiographed log viaat least one detector; determining differences in radiation attenuationbetween a portion of the log having no objects therein and a portioncontaining objects, from pixel-specific attenuation obtained via aradiographic projection from said at least one direction; determiningpositive and negative divergences in attenuation differences;andcalculating the presence of a knot mass in the log based on a knowledgeof known geometry and density of knots and stemwood, wherein the effectsof stemwood on the calculation are removed due to the elimination ofstemwood effects from said at least one radiographic projection byaverage or median filtering.
 5. The method of claim 4, wherein theattenuation differences are compared in a plane which is transverse tothe log as well as to a known direction of growth in the log.
 6. Themethod of claim 4,wherein said radiographing is performed by threeradiation sources equally spaced from one another in circumferentialrelation to the log, each providing a plurality of radiographicprojections representing a possible knot mass which are detected bycorresponding detectors of a detector array, and wherein the presenceand approximate location of knots and stemwood in the log are initiallyidentified by information from said plurality of radiographicprojections.
 7. The method of claim 6,wherein said plurality ofradiographic projections representing a possible knot mass are convertedinto volumetric elements of a cylindrical coordinate system, eachvolumetric element assigned a truth value which, when combined, provideinformation to calculate the direction of knots in said log; and whereinarray sums are calculated from said detector array to determinepositions of knots in said log.
 8. A method of analyzing a log todetermine the presence of objects constituting at least stemwood andknots inside the log, comprising:radiographing the log with threeequally spaced radiation sources to provide three radiographicprojections which contain X-ray attenuation data; performing average ormedian filtering to eliminate the effects of stemwood from an image ofthe object resulting from said three radiographic projections;re-projecting said three filtered radiographic projections onto a 3-Dcylindrical coordinate system by using predetermined coefficients todivide the object into volumetric elements, each element indicative of adensity value of the object; converting the density values into evidencevalues which give a probability as to whether a volumetric element ispart of a knot; and combining the evidence values to form an aggregateevidence value for a sector, wherein the direction, size and location ofthe object is determined in accordance with the sector having thelargest evidence values.
 9. The method of claim 8, furthercomprisingidentifying an initial presence of a possible object in thelog from the attenuation data, wherein the radiographic projections areconverted into volumetric elements representative of a 3-D cylindricalcoordinate system, and wherein truth values are assigned to eachvolumetric element and combined to obtain a truth value for a sector ofthe object; and determining an initial approximate position of theobject from the calculation of array sums from the radiation received bya detector array, wherein said steps of identifying and determining areperformed prior to said step of filtering to provide an initial estimateof the presence and location of the object in a log.
 10. The method ofclaim 8,wherein said attenuation data is used to determine attenuationdifferences between portions of the log which contain no objects, andportions of the log containing the object; and wherein said attenuationdifferences are compared in a direction which is transverse to both thelog and to a known direction of growth of the log.
 11. The method ofclaim 10, wherein divergences obtained from the attenuation differencesare identified via the use of logical inference rules.